Instructions to use subhash05/eagle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use subhash05/eagle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("subhash05/eagle", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- df7f2149041cc3b3e4f42211ffcddc9345e946d996c16d5c6ab8ad6c6df1e56e
- Size of remote file:
- 246 MB
- SHA256:
- 28b49a64b15f055ae6cea1d009b926133d21eff8dda46329f023c422c5654930
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